Participant stats

ageGroup	mean_age	se_age	N
Children	10.4	0.2691	30

Adolescents 15.46 0.2488 30

Adults 21.9 0.3939 30

ageGroup	gender	n
Children	0	14
Children	1	16
Adolescents	0	14
Adolescents	1	16
Adults	0	15
Adults	1	15

race	n	prop_race
Asian	22	0.2444
Black	10	0.1111
Mixed Race	24	0.2667
Native American	2	0.02222
White	32	0.3556

hispanic	n	prop_hisp
0	74	0.8222
1	16	0.1778

data_type	block	freq	pa	mem	fr
behav	1	89	90	90	90
neur	1	88	90	90	NA
behav	2	87	87	86	86
neur	2	85	82	82	NA

Relation between age and IQ

Should quadratic age be included in the model?

No, including quadratic age does not improve model fit.

Is there a relation between age and IQ?

## 
## Call:
## lm(formula = IQ ~ age_scaled, data = subList)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -22.839  -9.665  -1.361   8.357  34.440 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  110.589      1.295   85.38   <2e-16 ***
## age_scaled    -2.996      1.303   -2.30   0.0238 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 12.29 on 88 degrees of freedom
## Multiple R-squared:  0.0567, Adjusted R-squared:  0.04599 
## F-statistic:  5.29 on 1 and 88 DF,  p-value: 0.02381

There is a relation between age and IQ in the dataset. We will include IQ as an interacting fixed effect in all subsequent analyses to control for it.

Frequency-learning

Plot: Response accuracy by age group and appearance count

ageGroup	freqTrialType	N	freqAcc	sd	se	ci
Children	new	1186	0.8272	0.3783	0.01098	0.02155
Children	old	2355	0.8896	0.3135	0.006459	0.01267
Adolescents	new	1332	0.9099	0.2864	0.007848	0.0154
Adolescents	old	2675	0.9215	0.269	0.005201	0.0102
Adults	new	1353	0.9623	0.1905	0.00518	0.01016
Adults	old	2732	0.9535	0.2106	0.004029	0.0079

freqTrialType	N	freqAcc	sd	se	ci
new	3871	0.9029	0.2962	0.00476	0.009333
old	7762	0.9231	0.2665	0.003025	0.005929

Model: Frequency learning response accuracy: new items

## Fitting 4 (g)lmer() models:
## [....]

## Mixed Model Anova Table (Type 3 tests, LRT-method)
## 
## Model: freqAcc ~ ageScaled * IQScaled + (1 | sub)
## Data: freqDataNewItems
## Df full model: 5
##               Effect df     Chisq p.value
## 1          ageScaled  1 21.84 ***   <.001
## 2           IQScaled  1    5.41 *    .020
## 3 ageScaled:IQScaled  1      2.60    .107
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1

	freq Acc
Predictors	Estimates	CI	p
(Intercept)	3.15	2.79 – 3.51	<0.001
ageScaled	0.87	0.52 – 1.22	<0.001
IQScaled	0.42	0.07 – 0.77	0.020
ageScaled * IQScaled	0.27	-0.06 – 0.61	0.110
Random Effects
σ²	3.29
τ₀₀ _sub	1.59
ICC	0.33
N _sub	90
Marginal R² / Conditional R²	0.166 / 0.438

Model: Frequency learning response accuracy - repeated items

## Fitting 8 (g)lmer() models:
## [........]

## Mixed Model Anova Table (Type 3 tests, LRT-method)
## 
## Model: freqAcc ~ appearanceCountScaled * ageScaled * IQScaled + (appearanceCountScaled | 
## Model:     sub)
## Data: freqDataOldItems
## Df full model: 11
##                                     Effect df      Chisq p.value
## 1                    appearanceCountScaled  1 142.05 ***   <.001
## 2                                ageScaled  1  34.80 ***   <.001
## 3                                 IQScaled  1     6.05 *    .014
## 4          appearanceCountScaled:ageScaled  1  19.14 ***   <.001
## 5           appearanceCountScaled:IQScaled  1       0.00    .949
## 6                       ageScaled:IQScaled  1       0.06    .809
## 7 appearanceCountScaled:ageScaled:IQScaled  1       0.06    .805
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1

	freq Acc
Predictors	Estimates	CI	p
(Intercept)	3.80	3.44 – 4.15	<0.001
appearanceCountScaled	1.54	1.30 – 1.79	<0.001
ageScaled	0.98	0.65 – 1.31	<0.001
IQScaled	0.41	0.08 – 0.74	0.015
appearanceCountScaled * ageScaled	0.47	0.26 – 0.68	<0.001
appearanceCountScaled * IQScaled	0.01	-0.21 – 0.22	0.950
ageScaled * IQScaled	0.04	-0.28 – 0.36	0.810
(appearanceCountScaled ageScaled) IQScaled	-0.03	-0.24 – 0.19	0.805
Random Effects
σ²	3.29
τ₀₀ _sub	1.09
τ₁₁ _{sub.re1.appearanceCountScaled}	0.23
ρ₀₁ _sub	0.90
ICC	0.25
N _sub	90
Marginal R² / Conditional R²	0.451 / 0.588

Plot: Frequency learning reaction times by appearance count

Model: Frequency learning reaction times - new items

## Fitting one lmer() model. [DONE]
## Calculating p-values. [DONE]

## Mixed Model Anova Table (Type 3 tests, S-method)
## 
## Model: freqTaskRT ~ (ageScaled + ageSquaredScaled) * IQScaled + (1 | 
## Model:     sub)
## Data: freqRTDataNewItems
##                      Effect       df       F p.value
## 1                 ageScaled 1, 82.13 7.87 **    .006
## 2          ageSquaredScaled 1, 80.92  4.13 *    .045
## 3                  IQScaled 1, 79.15    1.79    .185
## 4        ageScaled:IQScaled 1, 79.59  4.80 *    .031
## 5 ageSquaredScaled:IQScaled 1, 78.94  4.27 *    .042
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1

	freq Task RT
Predictors	Estimates	CI	p
(Intercept)	1.11	1.09 – 1.14	<0.001
ageScaled	-0.27	-0.45 – -0.08	0.006
ageSquaredScaled	0.19	0.01 – 0.38	0.045
IQScaled	-0.02	-0.05 – 0.01	0.185
ageScaled * IQScaled	-0.22	-0.42 – -0.02	0.031
ageSquaredScaled * IQScaled	0.20	0.01 – 0.39	0.042
Random Effects
σ²	0.08
τ₀₀ _sub	0.01
ICC	0.14
N _sub	90
Marginal R² / Conditional R²	0.083 / 0.209

Model: Frequency learning reaction times - repeated items

## Fitting one lmer() model. [DONE]
## Calculating p-values. [DONE]

## Mixed Model Anova Table (Type 3 tests, S-method)
## 
## Model: freqTaskRT ~ (ageScaled + ageSquaredScaled) * IQScaled * appearanceCountScaled + 
## Model:     (appearanceCountScaled | sub)
## Data: freqRTDataOldItems
##                                             Effect       df          F p.value
## 1                                        ageScaled 1, 83.93  13.39 ***   <.001
## 2                                 ageSquaredScaled 1, 83.48    8.99 **    .004
## 3                                         IQScaled 1, 82.87     5.88 *    .017
## 4                            appearanceCountScaled 1, 74.38 291.95 ***   <.001
## 5                               ageScaled:IQScaled 1, 82.94     3.84 +    .053
## 6                        ageSquaredScaled:IQScaled 1, 82.67     3.89 +    .052
## 7                  ageScaled:appearanceCountScaled 1, 80.58       0.39    .535
## 8           ageSquaredScaled:appearanceCountScaled 1, 78.24       0.26    .611
## 9                   IQScaled:appearanceCountScaled 1, 75.13       0.06    .807
## 10        ageScaled:IQScaled:appearanceCountScaled 1, 76.59       0.27    .606
## 11 ageSquaredScaled:IQScaled:appearanceCountScaled 1, 75.02       0.34    .559
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1

	freq Task RT
Predictors	Estimates	CI	p
(Intercept)	1.03	1.00 – 1.06	<0.001
ageScaled	-0.36	-0.55 – -0.17	<0.001
ageSquaredScaled	0.30	0.10 – 0.49	0.004
IQScaled	-0.04	-0.06 – -0.01	0.017
appearanceCountScaled	-0.08	-0.09 – -0.07	<0.001
ageScaled * IQScaled	-0.21	-0.41 – 0.00	0.053
ageSquaredScaled * IQScaled	0.20	0.00 – 0.40	0.052
ageScaled * appearanceCountScaled	-0.02	-0.09 – 0.05	0.535
ageSquaredScaled * appearanceCountScaled	0.02	-0.05 – 0.08	0.611
IQScaled * appearanceCountScaled	0.00	-0.01 – 0.01	0.807
(ageScaled * IQScaled) * appearanceCountScaled	-0.02	-0.09 – 0.05	0.606
(ageSquaredScaled IQScaled) appearanceCountScaled	0.02	-0.05 – 0.09	0.559
Random Effects
σ²	0.07
τ₀₀ _sub	0.02
τ₁₁ _{sub.re1.appearanceCountScaled}	0.00
ρ₀₁ _sub	0.36
ICC	0.18
N _sub	90
Marginal R² / Conditional R²	0.150 / 0.306

Frequency reports

Plot: Frequency report histograms

Plot: Frequency report error magnitudes

Table: Frequency report error magnitude descriptive stats

ageGroup	N	rep_error_mag	sd	se	ci
Children	1290	1.457	1.317	0.03667	0.07194
Adolescents	1383	1.095	1.112	0.0299	0.05865
Adults	1434	1.124	1.046	0.02762	0.05418

Model: Frequency report error magnitudes by age and frequency condition

## Fitting one lmer() model. [DONE]
## Calculating p-values. [DONE]

## Mixed Model Anova Table (Type 3 tests, S-method)
## 
## Model: rep_error_mag ~ (ageScaled + ageSquaredScaled) * IQScaled * freqCond + 
## Model:     (freqCond | sub)
## Data: freqReports
##                                Effect       df         F p.value
## 1                           ageScaled 1, 83.86 12.50 ***   <.001
## 2                    ageSquaredScaled 1, 83.50   8.73 **    .004
## 3                            IQScaled 1, 84.73  10.18 **    .002
## 4                            freqCond 1, 83.72      0.08    .773
## 5                  ageScaled:IQScaled 1, 83.26      0.19    .667
## 6           ageSquaredScaled:IQScaled 1, 82.97      0.06    .813
## 7                  ageScaled:freqCond 1, 83.91      0.04    .839
## 8           ageSquaredScaled:freqCond 1, 83.72      0.01    .917
## 9                   IQScaled:freqCond 1, 84.38      0.25    .622
## 10        ageScaled:IQScaled:freqCond 1, 83.54      0.47    .495
## 11 ageSquaredScaled:IQScaled:freqCond 1, 83.39      0.28    .600
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1

	rep error mag
Predictors	Estimates	CI	p
(Intercept)	1.20	1.13 – 1.28	<0.001
ageScaled	-0.98	-1.53 – -0.44	0.001
ageSquaredScaled	0.81	0.27 – 1.35	0.004
IQScaled	-0.13	-0.21 – -0.05	0.002
freqCond [1]	-0.02	-0.13 – 0.10	0.773
ageScaled * IQScaled	-0.13	-0.70 – 0.45	0.667
ageSquaredScaled * IQScaled	0.07	-0.48 – 0.61	0.813
ageScaled * freqCond [1]	-0.08	-0.87 – 0.71	0.839
ageSquaredScaled * freqCond [1]	0.04	-0.74 – 0.83	0.917
IQScaled * freqCond [1]	-0.03	-0.14 – 0.09	0.622
(ageScaled * IQScaled) * freqCond [1]	-0.29	-1.12 – 0.54	0.495
(ageSquaredScaled IQScaled) freqCond [1]	0.21	-0.58 – 1.00	0.600
Random Effects
σ²	0.99
τ₀₀ _sub	0.10
τ₁₁ _{sub.re1.freqCond1}	0.24
ρ₀₁ _sub	0.66
ICC	0.09
N _sub	90
Marginal R² / Conditional R²	0.059 / 0.146

Associative memory

Plot: Memory performance by frequency condition: Individual subject data

Plot: Memory performance by frequency condition

Model: Memory performance by frequency condition

## Fitting 12 (g)lmer() models:
## [............]

## Mixed Model Anova Table (Type 3 tests, LRT-method)
## 
## Model: memAcc ~ freqCond * IQScaled * (ageScaled + ageSquaredScaled) + 
## Model:     (freqCond | sub)
## Data: memData
## Df full model: 15
##                                Effect df     Chisq p.value
## 1                            freqCond  1 21.56 ***   <.001
## 2                            IQScaled  1 13.98 ***   <.001
## 3                           ageScaled  1   8.75 **    .003
## 4                    ageSquaredScaled  1    4.37 *    .037
## 5                   freqCond:IQScaled  1      0.95    .331
## 6                  freqCond:ageScaled  1 11.14 ***   <.001
## 7           freqCond:ageSquaredScaled  1   9.62 **    .002
## 8                  IQScaled:ageScaled  1      0.09    .770
## 9           IQScaled:ageSquaredScaled  1      0.03    .852
## 10        freqCond:IQScaled:ageScaled  1      2.23    .136
## 11 freqCond:IQScaled:ageSquaredScaled  1      2.58    .108
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1

	mem Acc
Predictors	Estimates	CI	p
(Intercept)	0.27	0.14 – 0.39	<0.001
freqCond [1]	-0.22	-0.30 – -0.13	<0.001
IQScaled	0.26	0.13 – 0.39	<0.001
ageScaled	1.38	0.49 – 2.27	0.002
ageSquaredScaled	-0.95	-1.84 – -0.07	0.034
freqCond [1] * IQScaled	-0.04	-0.14 – 0.05	0.329
freqCond [1] * ageScaled	-1.07	-1.69 – -0.46	0.001
freqCond [1] * ageSquaredScaled	0.99	0.38 – 1.60	0.001
IQScaled * ageScaled	0.14	-0.79 – 1.07	0.770
IQScaled * ageSquaredScaled	-0.08	-0.97 – 0.80	0.852
(freqCond [1] * IQScaled) * ageScaled	-0.49	-1.13 – 0.15	0.133
(freqCond [1] * IQScaled) * ageSquaredScaled	0.51	-0.11 – 1.12	0.105
Random Effects
σ²	3.29
τ₀₀ _sub	0.22
τ₁₁ _{sub.freqCond1}	0.05
ρ₀₁ _sub	-0.27
ICC	0.08
N _sub	90
Marginal R² / Conditional R²	0.079 / 0.150

Plot: Memory performance by reported frequency

Model: Memory performance by reported frequency

## Fitting 12 (g)lmer() models:
## [............]

## Mixed Model Anova Table (Type 3 tests, LRT-method)
## 
## Model: memAcc ~ freqReportScaled * (ageScaled + ageSquaredScaled) * 
## Model:     IQScaled + (freqReportScaled | sub)
## Data: memFreqData
## Df full model: 15
##                                        Effect df     Chisq p.value
## 1                            freqReportScaled  1 32.41 ***   <.001
## 2                                   ageScaled  1   9.23 **    .002
## 3                            ageSquaredScaled  1    4.69 *    .030
## 4                                    IQScaled  1 13.90 ***   <.001
## 5                  freqReportScaled:ageScaled  1  10.19 **    .001
## 6           freqReportScaled:ageSquaredScaled  1   9.51 **    .002
## 7                   freqReportScaled:IQScaled  1      0.15    .698
## 8                          ageScaled:IQScaled  1      0.05    .825
## 9                   ageSquaredScaled:IQScaled  1      0.02    .901
## 10        freqReportScaled:ageScaled:IQScaled  1      0.85    .357
## 11 freqReportScaled:ageSquaredScaled:IQScaled  1      0.73    .394
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1

	mem Acc
Predictors	Estimates	CI	p
(Intercept)	0.26	0.13 – 0.39	<0.001
freqReportScaled	0.28	0.19 – 0.37	<0.001
ageScaled	1.44	0.53 – 2.35	0.002
ageSquaredScaled	-1.01	-1.91 – -0.11	0.028
IQScaled	0.26	0.13 – 0.39	<0.001
freqReportScaled * ageScaled	1.11	0.45 – 1.77	0.001
freqReportScaled * ageSquaredScaled	-1.06	-1.72 – -0.40	0.002
freqReportScaled * IQScaled	0.02	-0.07 – 0.11	0.697
ageScaled * IQScaled	0.11	-0.85 – 1.06	0.825
ageSquaredScaled * IQScaled	-0.06	-0.96 – 0.85	0.901
(freqReportScaled ageScaled) IQScaled	0.33	-0.37 – 1.04	0.356
(freqReportScaled ageSquaredScaled) IQScaled	-0.29	-0.97 – 0.38	0.393
Random Effects
σ²	3.29
τ₀₀ _sub	0.23
τ₁₁ _{sub.re1.freqReportScaled}	0.05
ρ₀₁ _sub	-0.14
ICC	0.07
N _sub	90
Marginal R² / Conditional R²	0.089 / 0.149

Model: Comparison of frequency report vs. frequency condition as predictors

## Fitting 12 (g)lmer() models:
## [............]

Brain-behavior relations

Overall PFC activity during encoding

Model: Overall PFC activity by age

## 
## Call:
## lm(formula = mean_pfc_scaled ~ ageScaled * IQScaled, data = mem_means)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.4400 -0.4993 -0.1544  0.4341  3.6432 
## 
## Coefficients:
##                     Estimate Std. Error t value Pr(>|t|)   
## (Intercept)        -0.003747   0.103171  -0.036   0.9711   
## ageScaled           0.312379   0.105307   2.966   0.0039 **
## IQScaled           -0.100595   0.108795  -0.925   0.3577   
## ageScaled:IQScaled -0.015912   0.100431  -0.158   0.8745   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9527 on 86 degrees of freedom
## Multiple R-squared:  0.1229, Adjusted R-squared:  0.09235 
## F-statistic: 4.018 on 3 and 86 DF,  p-value: 0.009992

PFC activity during encoding increases with age.

Model: Memory difference scores by overall PFC activity

## 
## Call:
## lm(formula = mem_diff ~ mean_pfc_scaled * (ageScaled + ageSquaredScaled) * 
##     IQScaled, data = mem_means)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.45614 -0.09792  0.01422  0.12575  0.37304 
## 
## Coefficients:
##                                           Estimate Std. Error t value Pr(>|t|)
## (Intercept)                                0.08916    0.02322   3.840 0.000249
## mean_pfc_scaled                           -0.01706    0.02778  -0.614 0.540893
## ageScaled                                  0.46936    0.16965   2.767 0.007068
## ageSquaredScaled                          -0.41339    0.16720  -2.472 0.015595
## IQScaled                                   0.01193    0.02753   0.433 0.666070
## mean_pfc_scaled:ageScaled                  0.06497    0.20251   0.321 0.749198
## mean_pfc_scaled:ageSquaredScaled          -0.07122    0.19928  -0.357 0.721749
## mean_pfc_scaled:IQScaled                   0.05025    0.02560   1.963 0.053181
## ageScaled:IQScaled                         0.10497    0.18589   0.565 0.573918
## ageSquaredScaled:IQScaled                 -0.13334    0.17215  -0.775 0.440933
## mean_pfc_scaled:ageScaled:IQScaled         0.07302    0.18481   0.395 0.693853
## mean_pfc_scaled:ageSquaredScaled:IQScaled -0.06293    0.17427  -0.361 0.719010
##                                              
## (Intercept)                               ***
## mean_pfc_scaled                              
## ageScaled                                 ** 
## ageSquaredScaled                          *  
## IQScaled                                     
## mean_pfc_scaled:ageScaled                    
## mean_pfc_scaled:ageSquaredScaled             
## mean_pfc_scaled:IQScaled                  .  
## ageScaled:IQScaled                           
## ageSquaredScaled:IQScaled                    
## mean_pfc_scaled:ageScaled:IQScaled           
## mean_pfc_scaled:ageSquaredScaled:IQScaled    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.1801 on 78 degrees of freedom
## Multiple R-squared:   0.24,  Adjusted R-squared:  0.1329 
## F-statistic:  2.24 on 11 and 78 DF,  p-value: 0.02011

Overall PFC activity at encoding does not relate to memory difference scores.

PFC modulation (high vs. low frequency) during encoding

Model: PFC modulation by age

## 
## Call:
## lm(formula = freq_pfc_scaled ~ (ageScaled + ageSquaredScaled) * 
##     IQScaled, data = mem_means)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.6908 -0.4703 -0.0221  0.4317  2.3765 
## 
## Coefficients:
##                            Estimate Std. Error t value Pr(>|t|)   
## (Intercept)                0.003983   0.105036   0.038  0.96984   
## ageScaled                  1.968308   0.742881   2.650  0.00963 **
## ageSquaredScaled          -1.727762   0.734172  -2.353  0.02094 * 
## IQScaled                   0.255117   0.109207   2.336  0.02187 * 
## ageScaled:IQScaled         0.933054   0.788859   1.183  0.24023   
## ageSquaredScaled:IQScaled -1.020836   0.745112  -1.370  0.17432   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9374 on 84 degrees of freedom
## Multiple R-squared:  0.1706, Adjusted R-squared:  0.1213 
## F-statistic: 3.457 on 5 and 84 DF,  p-value: 0.006871

PFC activity increases non-linearly with age.

Plot: PFC modulation by age

Mediation: Does PFC modulation mediate the relation between age and memory difference scores?

## 
## Call:
## lm(formula = mem_diff_scaled ~ (ageScaled + ageSquaredScaled) + 
##     IQScaled, data = mem_means)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.3635 -0.4731  0.1124  0.6351  1.9283 
## 
## Coefficients:
##                    Estimate Std. Error t value Pr(>|t|)    
## (Intercept)       2.655e-16  9.870e-02   0.000 1.000000    
## ageScaled         2.515e+00  7.156e-01   3.514 0.000706 ***
## ageSquaredScaled -2.306e+00  7.114e-01  -3.242 0.001690 ** 
## IQScaled          4.205e-02  1.035e-01   0.406 0.685672    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9364 on 86 degrees of freedom
## Multiple R-squared:  0.1528, Adjusted R-squared:  0.1232 
## F-statistic: 5.169 on 3 and 86 DF,  p-value: 0.002479

## 
## Call:
## lm(formula = freq_pfc_scaled ~ (ageScaled + ageSquaredScaled) + 
##     IQScaled, data = mem_means)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.59947 -0.49578 -0.02494  0.46327  2.51953 
## 
## Coefficients:
##                    Estimate Std. Error t value Pr(>|t|)   
## (Intercept)       4.802e-16  9.986e-02   0.000  1.00000   
## ageScaled         2.047e+00  7.239e-01   2.828  0.00582 **
## ageSquaredScaled -1.813e+00  7.197e-01  -2.519  0.01361 * 
## IQScaled          2.162e-01  1.047e-01   2.064  0.04206 * 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9473 on 86 degrees of freedom
## Multiple R-squared:  0.1329, Adjusted R-squared:  0.1026 
## F-statistic: 4.392 on 3 and 86 DF,  p-value: 0.006336

## 
## Call:
## lm(formula = mem_diff_scaled ~ (ageScaled + ageSquaredScaled) + 
##     IQScaled + freq_pfc_scaled, data = mem_means)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.3623 -0.5731  0.1874  0.5703  1.9681 
## 
## Coefficients:
##                    Estimate Std. Error t value Pr(>|t|)   
## (Intercept)       1.272e-16  9.497e-02   0.000  1.00000   
## ageScaled         1.925e+00  7.198e-01   2.674  0.00898 **
## ageSquaredScaled -1.784e+00  7.094e-01  -2.515  0.01378 * 
## IQScaled         -2.022e-02  1.021e-01  -0.198  0.84345   
## freq_pfc_scaled   2.880e-01  1.026e-01   2.809  0.00617 **
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.901 on 85 degrees of freedom
## Multiple R-squared:  0.2247, Adjusted R-squared:  0.1882 
## F-statistic: 6.159 on 4 and 85 DF,  p-value: 0.0002116

## 
## Causal Mediation Analysis 
## 
## Nonparametric Bootstrap Confidence Intervals with the Percentile Method
## 
##                Estimate 95% CI Lower 95% CI Upper p-value    
## ACME             0.5897       0.0832         1.36   0.018 *  
## ADE              1.9250       0.5464         3.52   0.002 ** 
## Total Effect     2.5148       1.2772         4.09  <2e-16 ***
## Prop. Mediated   0.2345       0.0435         0.63   0.018 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Sample Size Used: 90 
## 
## 
## Simulations: 1000

Overall, this suggests that PFC activity mediates the relation between age and memory difference scores, while controlling for IQ and quadratic age.

Mediation: Does the mediation hold without controlling for IQ and quadratic age?

## 
## Call:
## lm(formula = mem_diff_scaled ~ ageScaled, data = mem_means)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.09277 -0.59905  0.08106  0.55038  2.20419 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)  
## (Intercept) -3.017e-16  1.034e-01   0.000   1.0000  
## ageScaled    2.216e-01  1.040e-01   2.131   0.0358 *
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9807 on 88 degrees of freedom
## Multiple R-squared:  0.04909,    Adjusted R-squared:  0.03829 
## F-statistic: 4.543 on 1 and 88 DF,  p-value: 0.03584

## 
## Call:
## lm(formula = freq_pfc_scaled ~ (ageScaled), data = mem_means)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -2.19130 -0.57372 -0.09097  0.53884  2.97884 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)  
## (Intercept) 2.059e-17  1.038e-01   0.000   1.0000  
## ageScaled   2.009e-01  1.044e-01   1.924   0.0576 .
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9852 on 88 degrees of freedom
## Multiple R-squared:  0.04036,    Adjusted R-squared:  0.02946 
## F-statistic: 3.701 on 1 and 88 DF,  p-value: 0.0576

## 
## Call:
## lm(formula = mem_diff_scaled ~ ageScaled + freq_pfc_scaled, data = mem_means)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.1401 -0.5153  0.1855  0.5474  2.2187 
## 
## Coefficients:
##                   Estimate Std. Error t value Pr(>|t|)    
## (Intercept)     -3.088e-16  9.759e-02   0.000 1.000000    
## ageScaled        1.526e-01  1.002e-01   1.524 0.131224    
## freq_pfc_scaled  3.431e-01  1.002e-01   3.425 0.000941 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9259 on 87 degrees of freedom
## Multiple R-squared:  0.162,  Adjusted R-squared:  0.1428 
## F-statistic: 8.412 on 2 and 87 DF,  p-value: 0.0004571

## 
## Causal Mediation Analysis 
## 
## Nonparametric Bootstrap Confidence Intervals with the Percentile Method
## 
##                Estimate 95% CI Lower 95% CI Upper p-value   
## ACME            0.06893      0.00793         0.15   0.018 * 
## ADE             0.15264     -0.00942         0.34   0.068 . 
## Total Effect    0.22157      0.04848         0.40   0.002 **
## Prop. Mediated  0.31108      0.04530         1.15   0.016 * 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Sample Size Used: 90 
## 
## 
## Simulations: 1000

Yes, even without controlling for IQ and quadratic age, PFC activity mediates the relation between age and memory difference scores.

Mediation: Does age mediate the relation between PFC activity and memory difference scores?

## 
## Call:
## lm(formula = mem_diff_scaled ~ freq_pfc_scaled, data = mem_means)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.1637 -0.6345  0.1209  0.5906  2.1849 
## 
## Coefficients:
##                   Estimate Std. Error t value Pr(>|t|)    
## (Intercept)     -3.266e-16  9.832e-02    0.00 1.000000    
## freq_pfc_scaled  3.738e-01  9.887e-02    3.78 0.000285 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9328 on 88 degrees of freedom
## Multiple R-squared:  0.1397, Adjusted R-squared:  0.1299 
## F-statistic: 14.29 on 1 and 88 DF,  p-value: 0.000285

## 
## Call:
## lm(formula = ageScaled ~ freq_pfc_scaled, data = mem_means)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -1.5221 -0.8002 -0.1810  0.8057  2.0527 
## 
## Coefficients:
##                   Estimate Std. Error t value Pr(>|t|)  
## (Intercept)     -1.164e-16  1.038e-01   0.000   1.0000  
## freq_pfc_scaled  2.009e-01  1.044e-01   1.924   0.0576 .
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9852 on 88 degrees of freedom
## Multiple R-squared:  0.04036,    Adjusted R-squared:  0.02946 
## F-statistic: 3.701 on 1 and 88 DF,  p-value: 0.0576

## 
## Call:
## lm(formula = mem_diff_scaled ~ ageScaled + freq_pfc_scaled, data = mem_means)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.1401 -0.5153  0.1855  0.5474  2.2187 
## 
## Coefficients:
##                   Estimate Std. Error t value Pr(>|t|)    
## (Intercept)     -3.088e-16  9.759e-02   0.000 1.000000    
## ageScaled        1.526e-01  1.002e-01   1.524 0.131224    
## freq_pfc_scaled  3.431e-01  1.002e-01   3.425 0.000941 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9259 on 87 degrees of freedom
## Multiple R-squared:  0.162,  Adjusted R-squared:  0.1428 
## F-statistic: 8.412 on 2 and 87 DF,  p-value: 0.0004571

## 
## Causal Mediation Analysis 
## 
## Nonparametric Bootstrap Confidence Intervals with the Percentile Method
## 
##                Estimate 95% CI Lower 95% CI Upper p-value    
## ACME            0.03067     -0.00395         0.09   0.090 .  
## ADE             0.34308      0.16572         0.54   0.002 ** 
## Total Effect    0.37375      0.20412         0.57  <2e-16 ***
## Prop. Mediated  0.08205     -0.01107         0.27   0.090 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Sample Size Used: 90 
## 
## 
## Simulations: 1000

No, age does not significantly mediate the relation between PFC activity and memory difference scores.

Caudate modulation (high vs. low frequency) during encoding

Model: Caudate modulation by age

## 
## Call:
## lm(formula = freq_caudate_scaled ~ (ageScaled) * IQScaled, data = mem_means)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -1.7597 -0.7565 -0.1213  0.6429  2.5251 
## 
## Coefficients:
##                    Estimate Std. Error t value Pr(>|t|)   
## (Intercept)        -0.06833    0.10442  -0.654   0.5146   
## ageScaled           0.16490    0.10658   1.547   0.1255   
## IQScaled            0.18017    0.11011   1.636   0.1054   
## ageScaled:IQScaled -0.29019    0.10165  -2.855   0.0054 **
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9642 on 86 degrees of freedom
## Multiple R-squared:  0.1016, Adjusted R-squared:  0.07023 
## F-statistic: 3.241 on 3 and 86 DF,  p-value: 0.02597

## 
## Call:
## lm(formula = freq_caudate_scaled ~ (ageScaled + ageSquaredScaled) * 
##     IQScaled, data = mem_means)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -1.5662 -0.7761 -0.1246  0.6692  2.4036 
## 
## Coefficients:
##                           Estimate Std. Error t value Pr(>|t|)
## (Intercept)               -0.09623    0.10649  -0.904    0.369
## ageScaled                 -0.89710    0.75320  -1.191    0.237
## ageSquaredScaled           1.07857    0.74437   1.449    0.151
## IQScaled                   0.15101    0.11072   1.364    0.176
## ageScaled:IQScaled        -1.23382    0.79981  -1.543    0.127
## ageSquaredScaled:IQScaled  0.91947    0.75546   1.217    0.227
## 
## Residual standard error: 0.9504 on 84 degrees of freedom
## Multiple R-squared:  0.1474, Adjusted R-squared:  0.09669 
## F-statistic: 2.905 on 5 and 84 DF,  p-value: 0.01811

No.

Model: Memory difference scores by caudate modulation

## 
## Call:
## lm(formula = mem_diff ~ freq_caudate_scaled * (ageScaled + ageSquaredScaled) * 
##     IQScaled, data = mem_means)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.44055 -0.08054  0.02601  0.09904  0.38811 
## 
## Coefficients:
##                                               Estimate Std. Error t value
## (Intercept)                                    0.08092    0.02132   3.796
## freq_caudate_scaled                            0.01287    0.02293   0.561
## ageScaled                                      0.50687    0.14798   3.425
## ageSquaredScaled                              -0.47685    0.14613  -3.263
## IQScaled                                       0.02063    0.02180   0.946
## freq_caudate_scaled:ageScaled                  0.21480    0.15026   1.430
## freq_caudate_scaled:ageSquaredScaled          -0.19396    0.14375  -1.349
## freq_caudate_scaled:IQScaled                   0.02226    0.02284   0.974
## ageScaled:IQScaled                             0.07313    0.17029   0.429
## ageSquaredScaled:IQScaled                     -0.09326    0.15873  -0.588
## freq_caudate_scaled:ageScaled:IQScaled         0.21192    0.16543   1.281
## freq_caudate_scaled:ageSquaredScaled:IQScaled -0.23098    0.15550  -1.485
##                                               Pr(>|t|)    
## (Intercept)                                   0.000289 ***
## freq_caudate_scaled                           0.576360    
## ageScaled                                     0.000983 ***
## ageSquaredScaled                              0.001637 ** 
## IQScaled                                      0.346996    
## freq_caudate_scaled:ageScaled                 0.156835    
## freq_caudate_scaled:ageSquaredScaled          0.181144    
## freq_caudate_scaled:IQScaled                  0.332862    
## ageScaled:IQScaled                            0.668809    
## ageSquaredScaled:IQScaled                     0.558525    
## freq_caudate_scaled:ageScaled:IQScaled        0.203981    
## freq_caudate_scaled:ageSquaredScaled:IQScaled 0.141473    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.1776 on 78 degrees of freedom
## Multiple R-squared:  0.2605, Adjusted R-squared:  0.1562 
## F-statistic: 2.498 on 11 and 78 DF,  p-value: 0.009606

No.

Repetition suppression

Model: Repetition suppression and age

## Fitting one lmer() model. [DONE]
## Calculating p-values. [DONE]

## Fitting one lmer() model. [DONE]
## Calculating p-values. [DONE]

## Mixed Model Anova Table (Type 3 tests, S-method)
## 
## Model: phc_decrease ~ IQ_scaled * (age_scaled + age_squared_scaled) + 
## Model:     (1 | sub)
## Data: model1_data
##                         Effect       df      F p.value
## 1                    IQ_scaled 1, 80.05   0.87    .354
## 2                   age_scaled 1, 79.42 3.30 +    .073
## 3           age_squared_scaled 1, 79.05 4.28 *    .042
## 4         IQ_scaled:age_scaled 1, 81.53   0.61    .439
## 5 IQ_scaled:age_squared_scaled 1, 80.86   0.45    .504
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1

	phc decrease
Predictors	Estimates	CI	p
(Intercept)	44.40	36.66 – 52.13	<0.001
IQ_scaled	3.83	-4.23 – 11.90	0.354
age_scaled	-50.67	-105.32 – 3.98	0.073
age_squared_scaled	56.94	2.97 – 110.91	0.042
IQ_scaled * age_scaled	22.78	-34.58 – 80.15	0.439
IQ_scaled * age_squared_scaled	-18.53	-72.67 – 35.61	0.504
Random Effects
σ²	17188.80
τ₀₀ _sub	435.28
ICC	0.02
N _sub	88
Marginal R² / Conditional R²	0.008 / 0.032

Model: Repetition suppression and frequency reports

## Fitting one lmer() model. [DONE]
## Calculating p-values. [DONE]

## Fitting one lmer() model. [DONE]
## Calculating p-values. [DONE]

## Mixed Model Anova Table (Type 3 tests, S-method)
## 
## Model: freqReport ~ phc_decrease_scaled * IQ_scaled * age_scaled + (phc_decrease_scaled || 
## Model:     sub)
## Data: model2_data
##                                     Effect         df       F p.value
## 1                      phc_decrease_scaled 1, 1887.93    0.00    .974
## 2                                IQ_scaled   1, 83.46  4.68 *    .033
## 3                               age_scaled   1, 83.35 8.49 **    .005
## 4            phc_decrease_scaled:IQ_scaled 1, 1893.43    0.23    .635
## 5           phc_decrease_scaled:age_scaled 1, 1892.38    2.10    .147
## 6                     IQ_scaled:age_scaled   1, 83.58    1.07    .304
## 7 phc_decrease_scaled:IQ_scaled:age_scaled 1, 1896.46    0.04    .844
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1

	freq Report
Predictors	Estimates	CI	p
(Intercept)	4.45	4.29 – 4.62	<0.001
phc_decrease_scaled	0.00	-0.06 – 0.06	0.974
IQ_scaled	0.19	0.02 – 0.36	0.033
age_scaled	0.25	0.08 – 0.42	0.005
phc_decrease_scaled * IQ_scaled	0.02	-0.05 – 0.08	0.635
phc_decrease_scaled * age_scaled	0.05	-0.02 – 0.11	0.147
IQ_scaled * age_scaled	0.08	-0.08 – 0.25	0.304
(phc_decrease_scaled IQ_scaled) age_scaled	0.01	-0.05 – 0.07	0.844
Random Effects
σ²	1.59
τ₀₀ _sub	0.51
τ₀₀ _sub.1	0.00
N _sub	88
Marginal R² / Conditional R²	0.063 / NA

Model: Repetition suppression and associative memory

## Fitting 12 (g)lmer() models:
## [............]

## Mixed Model Anova Table (Type 3 tests, LRT-method)
## 
## Model: memAcc ~ phc_decrease_scaled * IQ_scaled * (age_scaled + age_squared_scaled) + 
## Model:     (phc_decrease_scaled || sub)
## Data: model3_data
## Df full model: 14
##                                              Effect df     Chisq p.value
## 1                               phc_decrease_scaled  1 10.86 ***   <.001
## 2                                         IQ_scaled  1 15.53 ***   <.001
## 3                                        age_scaled  1 18.60 ***   <.001
## 4                                age_squared_scaled  1 13.06 ***   <.001
## 5                     phc_decrease_scaled:IQ_scaled  1      0.01    .923
## 6                    phc_decrease_scaled:age_scaled  1      0.57    .451
## 7            phc_decrease_scaled:age_squared_scaled  1      1.29    .257
## 8                              IQ_scaled:age_scaled  1      1.10    .294
## 9                      IQ_scaled:age_squared_scaled  1      1.28    .258
## 10         phc_decrease_scaled:IQ_scaled:age_scaled  1      0.01    .938
## 11 phc_decrease_scaled:IQ_scaled:age_squared_scaled  1      0.07    .790
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1

	mem Acc
Predictors	Estimates	CI	p
(Intercept)	0.52	0.36 – 0.69	<0.001
phc_decrease_scaled	0.21	0.09 – 0.33	0.001
IQ_scaled	0.36	0.19 – 0.53	<0.001
age_scaled	2.69	1.52 – 3.86	<0.001
age_squared_scaled	-2.21	-3.36 – -1.05	<0.001
phc_decrease_scaled * IQ_scaled	-0.01	-0.13 – 0.12	0.922
phc_decrease_scaled * age_scaled	-0.33	-1.18 – 0.52	0.449
phc_decrease_scaled * age_squared_scaled	0.51	-0.36 – 1.37	0.254
IQ_scaled * age_scaled	0.65	-0.56 – 1.86	0.293
IQ_scaled * age_squared_scaled	-0.67	-1.82 – 0.49	0.256
(phc_decrease_scaled IQ_scaled) age_scaled	0.03	-0.82 – 0.89	0.937
(phc_decrease_scaled IQ_scaled) age_squared_scaled	0.11	-0.73 – 0.96	0.789
Random Effects
σ²	3.29
τ₀₀ _sub	0.31
τ₀₀ _sub.1	0.03
ICC	0.09
N _sub	88
Marginal R² / Conditional R²	0.117 / 0.193

Plot: Memory accuracy by repetition suppression

Model: Memory by repetition suppression and frequency reports

## Fitting 24 (g)lmer() models:
## [........................]

## Mixed Model Anova Table (Type 3 tests, LRT-method)
## 
## Model: memAcc ~ (age_scaled + age_squared_scaled) * IQ_scaled * phc_decrease_scaled * 
## Model:     freq_report_scaled + (phc_decrease_scaled * freq_report_scaled | 
## Model:     sub)
## Data: model4_data
## Df full model: 34
##                                                                 Effect df
## 1                                                           age_scaled  1
## 2                                                   age_squared_scaled  1
## 3                                                            IQ_scaled  1
## 4                                                  phc_decrease_scaled  1
## 5                                                   freq_report_scaled  1
## 6                                                 age_scaled:IQ_scaled  1
## 7                                         age_squared_scaled:IQ_scaled  1
## 8                                       age_scaled:phc_decrease_scaled  1
## 9                               age_squared_scaled:phc_decrease_scaled  1
## 10                                       IQ_scaled:phc_decrease_scaled  1
## 11                                       age_scaled:freq_report_scaled  1
## 12                               age_squared_scaled:freq_report_scaled  1
## 13                                        IQ_scaled:freq_report_scaled  1
## 14                              phc_decrease_scaled:freq_report_scaled  1
## 15                            age_scaled:IQ_scaled:phc_decrease_scaled  1
## 16                    age_squared_scaled:IQ_scaled:phc_decrease_scaled  1
## 17                             age_scaled:IQ_scaled:freq_report_scaled  1
## 18                     age_squared_scaled:IQ_scaled:freq_report_scaled  1
## 19                   age_scaled:phc_decrease_scaled:freq_report_scaled  1
## 20           age_squared_scaled:phc_decrease_scaled:freq_report_scaled  1
## 21                    IQ_scaled:phc_decrease_scaled:freq_report_scaled  1
## 22         age_scaled:IQ_scaled:phc_decrease_scaled:freq_report_scaled  1
## 23 age_squared_scaled:IQ_scaled:phc_decrease_scaled:freq_report_scaled  1
##        Chisq p.value
## 1  15.61 ***   <.001
## 2  11.16 ***   <.001
## 3   10.65 **    .001
## 4    8.84 **    .003
## 5  23.99 ***   <.001
## 6       1.51    .219
## 7       1.76    .185
## 8       0.09    .767
## 9       0.45    .504
## 10      0.00    .948
## 11      0.02    .889
## 12      0.01    .939
## 13      0.75    .386
## 14    2.77 +    .096
## 15      0.00    .990
## 16      0.11    .744
## 17      0.16    .687
## 18      0.47    .495
## 19      0.12    .730
## 20      0.13    .716
## 21      0.03    .861
## 22      2.56    .110
## 23    2.74 +    .098
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '+' 0.1 ' ' 1

	mem Acc
Predictors	Estimates	CI	p
(Intercept)	0.53	0.36 – 0.70	<0.001
age_scaled	2.54	1.33 – 3.76	<0.001
age_squared_scaled	-2.11	-3.32 – -0.91	0.001
IQ_scaled	0.31	0.13 – 0.48	0.001
phc_decrease_scaled	0.20	0.07 – 0.32	0.003
freq_report_scaled	0.32	0.20 – 0.45	<0.001
age_scaled * IQ_scaled	0.78	-0.46 – 2.03	0.218
age_squared_scaled * IQ_scaled	-0.81	-2.00 – 0.38	0.183
age_scaled * phc_decrease_scaled	-0.13	-1.01 – 0.74	0.766
age_squared_scaled * phc_decrease_scaled	0.31	-0.59 – 1.20	0.502
IQ_scaled * phc_decrease_scaled	-0.00	-0.14 – 0.13	0.947
age_scaled * freq_report_scaled	0.06	-0.83 – 0.96	0.889
age_squared_scaled * freq_report_scaled	-0.04	-0.94 – 0.87	0.939
IQ_scaled * freq_report_scaled	-0.06	-0.19 – 0.07	0.385
phc_decrease_scaled * freq_report_scaled	-0.12	-0.25 – 0.02	0.096
(age_scaled * IQ_scaled) * phc_decrease_scaled	-0.01	-0.90 – 0.89	0.990
(age_squared_scaled IQ_scaled) phc_decrease_scaled	0.15	-0.73 – 1.03	0.743
(age_scaled * IQ_scaled) * freq_report_scaled	-0.20	-1.18 – 0.77	0.686
(age_squared_scaled IQ_scaled) freq_report_scaled	0.33	-0.62 – 1.29	0.494
(age_scaled phc_decrease_scaled) freq_report_scaled	0.16	-0.73 – 1.04	0.728
(age_squared_scaled phc_decrease_scaled) freq_report_scaled	-0.17	-1.10 – 0.76	0.714
(IQ_scaled phc_decrease_scaled) freq_report_scaled	-0.01	-0.16 – 0.13	0.861
(age_scaled * IQ_scaled phc_decrease_scaled) freq_report_scaled	-0.88	-1.96 – 0.19	0.107
(age_squared_scaled IQ_scaled phc_decrease_scaled) * freq_report_scaled	0.92	-0.16 – 2.01	0.096
Random Effects
σ²	3.29
τ₀₀ _sub	0.32
τ₁₁ _{sub.re1.phc_decrease_scaled}	0.02
τ₁₁ _{sub.re1.freq_report_scaled}	0.00
τ₁₁ _{sub.re1.phc_decrease_scaled_by_freq_report_scaled}	0.02
ρ₀₁	-0.20
	0.70
	-0.99
N _sub	88
Marginal R² / Conditional R²	0.162 / NA

Developmental change in prefrontal cortex recruitment supports the emergence of value-guided memory

Kate Nussenbaum

1/26/21